Lightweight smoke identification method based on spatial-temporal feature fusion
The invention discloses a lightweight smoke identification method based on spatial-temporal feature fusion, and the method comprises the steps: firstly constructing a lightweight deep learning network (TSNet) of spatial-temporal feature fusion, and the network comprises a shallow spatial feature ext...
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| creator | PU JIANFEI JIANG HAOWEN WEI WEI |
| description | The invention discloses a lightweight smoke identification method based on spatial-temporal feature fusion, and the method comprises the steps: firstly constructing a lightweight deep learning network (TSNet) of spatial-temporal feature fusion, and the network comprises a shallow spatial feature extraction module and a spatial-temporal feature extraction module; and on the basis of the network, a lightweight smoke identification model based on spatial-temporal feature fusion is constructed. In the model, firstly, a shallow spatial feature extraction module in the TSNet is utilized to extract local spatial features of a single-frame picture, the local spatial features are abstracted, and the resolution of a feature map is reduced step by step; the method comprises the following steps: respectively extracting time sequence features among multiple frames of smoke pictures and deep abstract features of a single frame of smoke picture by using improved probsparse self-attention through a time-space feature extract |
| format | Patent |
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| title | Lightweight smoke identification method based on spatial-temporal feature fusion |
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